Proteins have been played an important role in a creature and the numbers of proteins and their structures have been increased with years. Since protein applications are more widely used, there will be a lot of problems to be solved.
Using a position-specific scoring matrix (PSSM) generated from PSI-BLAST in this thesis, we develop the modified fuzzy k-nearest neighbor method to predict the protein relative solvent accessibility. By modifying the membership functions of the fuzzy k-nearest neighbor method by Sim et al. [31], has recently been applied to protein solvent accessibility prediction with excellent results. Our modified fuzzy k-nearest neighbor method is applied on three-state, E, I, and B, and two-state, E, and B, relative solvent accessibility predictions, and its prediction accuracy compares favorly with those by the fuzzy k-NN and QuickRBF approaches. At last, we combine the prediction results of modified fuzzy k-nearest neighbor method and QuickRBF approach to improve the performance. Six modification approaches include: (1) Fuzzy K-Nearest Neighbor Method, (2) Modified Fuzzy K-Nearest Neighbor Method, (3) QuickRBF, (4) Linear Combination Fusion 1, (5) Linear Combination Fusion 2, and (6) Reliability Index Fusion. We recommend the Linear Combination Fusion 2 approach which has shown the best performance in most cases.